Best AI tools for< Collaborate With Scientists >

Kaggle is a platform for data science and machine learning enthusiasts to collaborate, learn, and compete. It offers a wide range of datasets, competitions, and notebooks for users to practice and showcase their skills. With a vibrant community of data scientists and experts, Kaggle provides a valuable resource for both beginners and professionals to enhance their knowledge and expertise in the field of data science and machine learning.

Strong Analytics is a data science consulting and machine learning engineering company that specializes in building bespoke data science, machine learning, and artificial intelligence solutions for various industries. They offer end-to-end services to design, engineer, and deploy custom AI products and solutions, leveraging a team of full-stack data scientists and engineers with cross-industry experience. Strong Analytics is known for its expertise in accelerating innovation, deploying state-of-the-art techniques, and empowering enterprises to unlock the transformative value of AI.

Connected Papers is a search engine for academic papers that uses artificial intelligence to help users find and explore relevant research. It allows users to search for papers by keyword, author, or title, and then explore the connections between them. Connected Papers also provides a variety of tools to help users organize and manage their research, including the ability to create custom collections of papers, add notes and annotations, and share their research with others.

DVC Studio is a collaboration tool for machine learning teams. It provides seamless data and model management, experiment tracking, visualization, and automation. DVC Studio is built for ML researchers, practitioners, and managers. It enables model organization and discovery across all ML projects and manages model lifecycle with Git, unifying ML projects with the best DevOps practices. DVC Studio also provides ML experiment tracking, visualization, collaboration, and automation using Git. It applies software engineering and DevOps best-practices to automate ML bookkeeping and model training, enabling easy collaboration and faster iterations.

Materiom is an AI-powered platform that supports the development of next-generation materials made from 100% biobased sources. It provides an open-access database of biomaterials recipes, facilitates collaboration among scientists, producers, and brands, and offers a genAI-powered tool to identify high-performing material alternatives quickly. The platform aims to create a materials economy that regenerates nature and promotes human health.

GeoSpy.ai is a web-based geospatial intelligence platform that provides users with access to a variety of geospatial data and tools. The platform allows users to create and share maps, analyze data, and collaborate with others. GeoSpy.ai is used by a variety of professionals, including law enforcement, intelligence analysts, and environmental scientists.

DagsHub is an open source data science collaboration platform that helps AI teams build better models and manage data projects. It provides a central location for data, code, experiments, and models, making it easy for teams to collaborate and track their progress. DagsHub also integrates with a variety of popular data science tools and frameworks, making it a powerful tool for data scientists and machine learning engineers.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

Weights & Biases is a machine learning platform that helps data scientists and engineers build, train, and deploy machine learning models. It provides a central location to track and manage all of your machine learning projects, and it offers a variety of tools to help you collaborate with others and share your work.

Deepnote is an AI-powered analytics and data science notebook platform designed for teams. It allows users to turn notebooks into powerful data apps and dashboards, combining Python, SQL, R, or even working without writing code at all. With Deepnote, users can query various data sources, generate code, explain code, and create interactive visualizations effortlessly. The platform offers features like collaborative workspaces, scheduling notebooks, deploying APIs, and integrating with popular data warehouses and databases. Deepnote prioritizes security and compliance, providing users with control over data access and encryption. It is loved by a community of data professionals and widely used in universities and by data analysts and scientists.

Coginiti is a collaborative analytics platform and tools designed for SQL developers, data scientists, engineers, and analysts. It offers capabilities such as AI assistant, data mesh, database & object store support, powerful query & analysis, and share & reuse curated assets. Coginiti empowers teams and organizations to manage collaborative practices, data efficiency, and deliver trusted data products faster. The platform integrates modular analytic development, collaborative versioned teamwork, and a data quality framework to enhance productivity and ensure data reliability. Coginiti also provides an AI-enabled virtual analytics advisor to boost team efficiency and empower data heroes.

Bay Area AI is a technical AI meetup group based in San Francisco, CA, consisting of startup engineers, research scientists, computational linguists, mathematicians, and philosophers. The group focuses on understanding the meaning of text, reasoning, and human intent through technology to build new businesses and enhance the human experience in the modern connected world. They work on building systems with Machine Learning on top of Data Pipelines, exploring open-source solutions, and modeling human behavior in industry for practical results.

Protocol Pal is a website designed to help users with building protocols. It is a user-friendly platform created by Basam Alasaly, Oceanexplains, and Tkruer. The website aims to simplify the process of creating protocols for various purposes. Users can easily navigate through the platform to generate structured protocols efficiently. Protocol Pal is a valuable tool for researchers, scientists, and professionals who require well-defined protocols for their work.

Streamlit is a web application framework that allows users to create interactive web applications with Python. It simplifies the process of building data-driven apps by providing a simple and intuitive way to create and share them. With Streamlit, users can easily turn data scripts into shareable web apps, making it ideal for data scientists, machine learning engineers, and developers looking to showcase their work.

DVC is an open-source platform for managing machine learning data and experiments. It provides a unified interface for working with data from various sources, including local files, cloud storage, and databases. DVC also includes tools for versioning data and experiments, tracking metrics, and automating compute resources. DVC is designed to make it easy for data scientists and machine learning engineers to collaborate on projects and share their work with others.

Rayyan is an intelligent systematic review tool trusted by over 500,000 researchers worldwide. It helps users organize, manage, and accelerate collaborative systematic literature reviews. Rayyan empowers users to work remotely and collaborate with distributed research teams, offering membership packages with onboarding, training, and priority support. The tool is designed to understand language, learn from user decisions, and facilitate quick navigation through systematic reviews. Rayyan also provides solutions for organizations and businesses to streamline research processes and save valuable researcher time.

Lychee is an all-in-one data platform designed to streamline the data workflow process, from data collection to analysis, visualization, and sharing. It offers powerful features such as instant graph generation, AI data analysis, website deployment, social media sharing, and team collaboration. Lychee aims to simplify complex data tasks and help users make faster progress in their data-related projects.

Fetch.ai Innovation Lab is a leading platform advancing artificial intelligence and driving innovation to create value at scale. The lab unites academic institutes, research teams, and businesses to develop and expand advanced AI solutions. It fosters a collaborative environment that supports impactful projects and pushes the boundaries of what's possible with AI. The lab offers resources, support, and networking opportunities to drive groundbreaking ideas and growth in the AI ecosystem.

HoloEye.AI is a transformative AI biological intelligence company that leverages cutting-edge artificial intelligence technology to revolutionize the field of biological research. The platform offers advanced AI solutions for analyzing complex biological data, enabling researchers to gain deeper insights and accelerate scientific discoveries.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

RAFT (Reusable Accelerated Functions and Tools) is a C++ header-only template library with an optional shared library that contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

ZenML is an extensible, open-source MLOps framework for creating portable, production-ready machine learning pipelines. By decoupling infrastructure from code, ZenML enables developers across your organization to collaborate more effectively as they develop to production.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

Supervisely is a computer vision platform that provides a range of tools and services for developing and deploying computer vision solutions. It includes a data labeling platform, a model training platform, and a marketplace for computer vision apps. Supervisely is used by a variety of organizations, including Fortune 500 companies, research institutions, and government agencies.

A curated list of Generative AI projects, tools, artworks, and models

LangGraph Studio is a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. It offers visual graphs and state editing to better understand agent workflows and iterate faster. Users can collaborate with teammates using LangSmith to debug failure modes. The tool integrates with LangSmith and requires Docker installed. Users can create and edit threads, configure graph runs, add interrupts, and support human-in-the-loop workflows. LangGraph Studio allows interactive modification of project config and graph code, with live sync to the interactive graph for easier iteration on long-running agents.

SwanLab is an open-source, lightweight AI experiment tracking tool that provides a platform for tracking, comparing, and collaborating on experiments, aiming to accelerate the research and development efficiency of AI teams by 100 times. It offers a friendly API and a beautiful interface, combining hyperparameter tracking, metric recording, online collaboration, experiment link sharing, real-time message notifications, and more. With SwanLab, researchers can document their training experiences, seamlessly communicate and collaborate with collaborators, and machine learning engineers can develop models for production faster.

Aider is an AI pair programming tool that allows users to collaborate with large language models (LLMs) to edit code in their local git repository. It works best with GPT-4o & Claude 3.5 Sonnet and can connect to almost any LLM. Users can run Aider with specific files, request changes, add new features or test cases, describe bugs, refactor code, update docs, and more. Aider automatically commits changes with sensible messages, supports multiple programming languages, and can handle complex requests by editing multiple files at once. It uses a map of the entire git repo for efficient performance in larger codebases. Users can chat with Aider, add images, URLs, and even code with their voice. Aider has achieved top scores on SWE Bench, solving real GitHub issues from popular open source projects like django, scikitlearn, matplotlib, etc.

Chatbox is a desktop client for ChatGPT, Claude, and other LLMs, providing a user-friendly interface for AI copilot assistance on Windows, Mac, and Linux. It offers features like local data storage, multiple LLM provider support, image generation with Dall-E-3, enhanced prompting, keyboard shortcuts, and more. Users can collaborate, access the tool on various platforms, and enjoy multilingual support. Chatbox is constantly evolving with new features to enhance the user experience.

This open-source project, also known as **Deep Learning System** or **AI System (AISys)**, aims to explore and learn about the system design of artificial intelligence and deep learning. The project is centered around the full-stack content of AI systems that ZOMI has accumulated,整理, and built during his work. The goal is to collaborate with all friends who are interested in AI open-source projects to jointly promote learning and discussion.

Co-LLM (Collaborative Language Models) is a tool for learning to decode collaboratively with multiple language models. It provides a method for data processing, training, and inference using a collaborative approach. The tool involves steps such as formatting/tokenization, scoring logits, initializing Z vector, deferral training, and generating results using multiple models. Co-LLM supports training with different collaboration pairs and provides baseline training scripts for various models. In inference, it uses 'vllm' services to orchestrate models and generate results through API-like services. The tool is inspired by allenai/open-instruct and aims to improve decoding performance through collaborative learning.

AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.

DVC, or Data Version Control, is a command-line tool and VS Code extension that helps you develop reproducible machine learning projects. With DVC, you can version your data and models, iterate fast with lightweight pipelines, track experiments in your local Git repo, compare any data, code, parameters, model, or performance plots, and share experiments and automatically reproduce anyone's experiment.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

Latitude is an open-source prompt engineering platform that helps developers and product teams build AI features with confidence. It simplifies prompt management, aids in testing AI responses, and provides detailed analytics on request performance. Latitude offers collaborative prompt management, support for advanced features, version control, API and SDKs for integration, observability, evaluations in batch or real-time, and is community-driven. It can be deployed on Latitude Cloud for a managed solution or self-hosted for control and customization.

Agenta is an open-source LLM developer platform for prompt engineering, evaluation, human feedback, and deployment of complex LLM applications. It provides tools for prompt engineering and management, evaluation, human annotation, and deployment, all without imposing any restrictions on your choice of framework, library, or model. Agenta allows developers and product teams to collaborate in building production-grade LLM-powered applications in less time.

Develops specialized materials, collaborating with scientists and utilizing CAD software expertise.

Doctoral dissertation advisor for project management and information technology. Use this as a guide to develop a dissertation plan for a master or doctoral degree program. Explore ideas and collaborate with your professor and collegues to generate your final disseration for review.

Advanced expert in fusion, superconductors, and materials with enhanced analytics and collaboration.

AI-to-AI direct communication mode

Deep learning researcher explaining Google Gemini from PDFs.

An expert MLOps engineer assisting in DevOps and pipeline optimization.

Chat with your Notion data!

Helps with creating Aero Projects

Make videos with MrBeast and Paddy Galloway

Assists in creating detailed briefs with examples on request.

Broadway-themed task coach with a musical twist.

A Smartsheet expert and consultant with a focus on coding and integration

Friendly planner for portrait shoots with creative ideas and photo references.

Design assistant for project refinement.

Expert TinyTap game creator for educational content.

Become A Famous Youtuber Like Mr. Beast

Ideas of unique tattoo designs

Guides software development processes through Kanban methodologies.

Figma Plugin Developer for Beginners